Estimation of Distribution Algorithms (EDAs)

Estimation of Distribution Algorithms (EDAs) are metaheuristics that iteratively build and refine a statistical model of the solution space and use this model to sample candidate solutions. The most well-known member of this family of algorithms is Ant Colony Optimization (ACO).

Publications

• Thomas Weise (汤卫思), Raymond Chiong, Jörg Lässig, Ke TANG (唐珂), Shigeyoshi Tsutsui, Wenxiang CHEN (陈文祥), Zbigniew Michalewicz, and Xin YAO (姚新): Benchmarking Optimization Algorithms: An Open Source Framework for the Traveling Salesman Problem. IEEE Computational Intelligence Magazine (CIM) 9(3):40-52. August 2014.
  TSP, TSP Suite, logistics, local search, EAs, MAs, ACO, EDAs, FFA, more infos.
• Thomas Weise (汤卫思), Stefan Niemczyk, Raymond Chiong, and Mingxu WAN (万明绪): A Framework for Multi-Model EDAs with Model Recombination. 4th European Event on Bio-Inspired Algorithms for Continuous Parameter Optimisation (EvoNUM'2011), part of Applications of Evolutionary Computation – Proceedings of EvoAPPLICATIONS 2011: EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, April 27-29, 2011, Torino, Italy, Part 1, Lecture Notes in Computer Science (LNCS), volume 6624, pages 304-313. Berlin, Germany: Springer-Verlag GmbH.
  EDAs, more infos.